text: from sklearn import tree
  
  #
  # input
  # 0 - bumpy
  # 1 - smoth
  #
  
  features = [[140, 1], [130, 1], [150, 0], [170, 0]]
  
  
  # output - what belongs to each feature
  # 0 - apple
  # 1 - orange
  labels = [0, 0, 1, 1]
  
  clf = tree.DecisionTreeClassifier()
  
  # train a classifier
  clf = clf.fit(features, labels)
  
  
  print(clf.predict([[150, 0]]))